# AC-VC: Non-parallel Low Latency Phonetic Posteriorgrams Based Voice Conversion

arXiv: https://arxiv.org/abs/2111.06601 · HTML: https://mlsanity.com/paper/2111.06601/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Nov 2021.

## Built on by (most cited first, 1 of 1)

- [ALO-VC: Any-to-any Low-latency One-shot Voice Conversion](https://mlsanity.com/paper/2306.01100/) (2023)

## Abstract (arXiv)

This paper presents AC-VC (Almost Causal Voice Conversion), a phonetic posteriorgrams based voice conversion system that can perform any-to-many voice conversion while having only 57.5 ms future look-ahead. The complete system is composed of three neural networks trained separately with non-parallel data. While most of the current voice conversion systems focus primarily on quality irrespective of algorithmic latency, this work elaborates on designing a method using a minimal amount of future context thus allowing a future real-time implementation. According to a subjective listening test organized in this work, the proposed AC-VC system achieves parity with the non-causal ASR-TTS baseline of the Voice Conversion Challenge 2020 in naturalness with a MOS of 3.5. In contrast, the results indicate that missing future context impacts speaker similarity. Obtained similarity percentage of 65% is lower than the similarity of current best voice conversion systems.